learning-to-learn

learning-to-learn is a skill for Claude Code, Codex from THU-MAIC/OpenMAIC. It costs 81 tokens per session (1,110 once invoked), scanned A, original, MIT.

A course-design guide that adds learning habits alongside the main subject topic. These habits include recalling information, explaining reasoning, predicting before checking, monitoring understanding and reviewing later.

In plain words
What is it for?
Adding practical learning actions to a concept lesson, such as answering from memory before looking, explaining why an answer works, checking a prediction and planning a later review.
Why use it?
It helps learners notice whether they really understand something, rather than mistaking familiarity for knowledge. The learning methods stay connected to the subject instead of becoming a separate lesson.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Adding practical learning actions to a concept lesson, such as answering from memory before looking, explaining why an answer works, checking a prediction and planning a later review.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/thu-maic/openmaic/learning-to-learn
About the project

OpenMAIC is a multi-agent classroom platform that uses agents to plan, build, and revise interactive courses from prompts and uploaded materials. It is designed for immersive learning experiences and supports course components such as slides, quizzes, interactives, projects, images, video, voices, and PowerPoint imports, with catalogue skills covering its workflows.

THU-MAIC/OpenMAIC · 32,590 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add THU-MAIC/OpenMAIC --skill learning-to-learn
Clone the repo
git clone --depth 1 https://github.com/THU-MAIC/OpenMAIC

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for learning-to-learn

README.md
[![agentmods](https://agentmods.dev/badge/skills/thu-maic/openmaic/learning-to-learn.svg)](https://agentmods.dev/skills/thu-maic/openmaic/learning-to-learn)
Your own site
<a href="https://agentmods.dev/skills/thu-maic/openmaic/learning-to-learn"><img src="https://agentmods.dev/badge/skills/thu-maic/openmaic/learning-to-learn.svg" alt="Measured on agentmods" height="20"></a>
Per session 81 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,110 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. ✓ AI security review Sonnet 5 · 6 Sept 2026 📄 Read the review Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00081 $0.01110
Opus 5 $0.00041 $0.00555
Sonnet 5 $0.00016 $0.00222
Haiku 4.5 $0.00008 $0.00111

Measured 8d ago against content hash fe8be28613d0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

learning-to-learn scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/agent-runtime/learning-to-learn/SKILL.md · 66 lines

What it actually says

学会学习(Learning to Learn)

把学习策略与元认知作为平行目标嵌入概念主课:不替换学科概念主线,而是改变学生如何经历、检查和巩固这些概念。

stage-design 仍然约束课堂的创建和持久化流程。如果同时使用 /understanding-by-design,先确定大概念、基本问题与表现性任务,再嵌入学习策略;如果同时使用 /social-emotional-learning,让两类平行目标服务同一概念任务,不要各自另起一条课程主线。

先声明平行目标

在页面计划前分别声明:

  1. 概念目标:学生最终要理解、解释或迁移什么;
  2. 学会学习目标:学生要练习哪一种学习动作,以及什么行为能证明它发生了。

每一个学习策略都要能回答“它在服务哪个概念理解”;答不出的嵌入删除。优先选择最贴合任务的 1–2 种策略,不要在一节课里罗列整套学习科学术语。

两条内容红线

  1. 规划标签不进页面学习缝元认知教学意图平行目标 等内部框架词只用于规划与 brief,不作为学生可见的标题、正文或栏目标签。
  2. 角色台词只走旁白:老师与学生代理的口述、示范和讨论发言放进 narration / actions;静态页面只承载概念要点、问题、任务与提示,不写“老师说”或“学生说”。

页面使用学生能立即执行的动作语言,而不是技术术语:

  • 检索练习:写成“别急着翻,先把答案写出来”;
  • 自我解释:写成“用自己的话给结论一个理由”;
  • 先预测后验证:写成“先猜一下,再看对不对”;
  • 间隔复习:写成“过几天再回来默一次”;
  • 监控理解:写成“你是真的懂,还是只是感觉懂了?”

只有当用户明确要求讲授某种学习方法本身时,才把对应术语作为学生要学的内容。

四个嵌入点

这些是页面规划锚点,不是页面标题,也不要求各自新增一页:

  1. 开场:正式讲解前,让学生先调取已有知识、做出初步判断或写下预测。
  2. 概念建立:得出结论后,让学生用自己的话解释一次,并追问“为什么”。学生代理可以示范不完整解释,再邀请学习者补充或质疑。
  3. 亲手做:在 interactive 中先预测或作答,再给反馈;错误要进入检查、补漏和重试路径,不能成为死路。
  4. 收束:同时收住“我理解了什么”“我是怎样学会的”“哪里还不确定”以及“之后如何再检索一次”。

多智能体的作用

  • 老师:示范先想再答、检查理解与定位缺口;认可“我卡住了”,再引导补漏。
  • 学生代理:呈现“感觉懂了但默不出来”、预测错误或解释不完整的真实状态,并邀请学习者判断、修正和迁移。

围绕方法和理解讨论,不评价人;老师及时把对话带回概念主线。

质量关口

  • 概念目标与学会学习目标分开声明。
  • 每个嵌入点都标明它服务的概念与可观察的学习动作。
  • 至少让学生实际经历一次主动回忆、自我解释或先预测后验证,而不是只听学习方法介绍。
  • 受挫与错误后保留反馈、补漏和重试路径。
  • 收束同时包含概念理解、学习过程反思与后续复习动作。
  • 逐页检查所有静态文字,不得出现内部规划标签或角色口述台词。
  • 不承诺“万能学习法”;需要比较研究证据时先核实来源。

边界

本 Skill 用于把学习策略嵌入学科概念课,不用于以学习方法或学习科学本身为内容主线的独立课程。若用户要把学习法做成第二条完整课程主线,先用 ask_user 确认范围。

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 66 lines · 81 tokens per session scan A fe8be28613d0

Subscribe to this mod's changes

learning-to-learn is a skill published in the GitHub repository THU-MAIC/OpenMAIC (32,590 stars, last pushed yesterday), licensed MIT. It adds 81 tokens to every session and 1,110 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

hr-onboarding

A new-hire onboarding plan as a single page — first week schedule, buddy + manager intro, learning track, equipment checklist, and "you're set when…" outcomes. Use when the brief mentions "onboarding", "new hire", "first week plan", or "入职".

nexu-io/open-design · 62 tokens

book-mirror

Take any book (EPUB/PDF), produce a personalized chapter-by-chapter analysis. Each chapter is preserved in detail (The Chapter) and mirrored back to the reader's actual life (The Mirror) using brain context. The mirror observes and resonates — a friend pointing out parallels, NOT a consultant rearranging the reader's…

garrytan/gbrain · 138 tokens

miniapp

Build a tiny interactive HTML playground only when someone asks to see, play with, or step through a mechanism.

yc-software/qm · 25 tokens

eli5

Explain research, papers, or technical ideas in plain English with minimal jargon, concrete analogies, and clear takeaways. Use when the user says "ELI5 this", asks for a simple explanation of a paper or research result, wants jargon removed, or asks what something technically dense actually means.

companion-inc/feynman · 63 tokens

deck-course-module

A course or workshop slide template with persistent learning goals, teaching pages, multiple-choice self-tests, and a wrap-up.

nexu-io/html-anything · 25 tokens

master-yinguang

A reference-based assistant for questions about Yinguang and Pure Land Buddhism, a Buddhist tradition focused on faith, ethical living, and practice connected with rebirth in the Pure Land. It can answer in Yinguang’s historical teaching style.

xr843/Master-skill · 274 tokens